When we had just classic databases, data warehouses, and stuff like data was managed sort of centrally, people had a very well-defined view of what was going on. It was very narrow in scope. That definition has been blown to smithereens. It’s like everything is enterprise data. It’s just ballooned. ... People are realizing that data for customer success is really important. That part is becoming more obvious to more people. If somebody comes to my website, and I take three days to respond to them, they’re going to be gone. But if I can respond to them in 30 seconds and say something intelligent, all of a sudden that interaction becomes much more valuable. My sales cycles become much shorter. The rest of it, concerning how to use the data to more efficiently run my business, however, is completely unclear at this point. ... Every time we do a new technology and all of a sudden people invest a ton in it, then you find your finance people are writing it off. This is no different. The data wave has been hyped so much that people are putting more and more money into it. They got to be like Google. They have to be like Facebook.
Banks are moving their core operations into the cloud at a rapid rate. But new tech brings new challenges
As with any concentrated market, there is a risk that cloud providers might start dictating their own terms, at the expense of the stability of the financial system. For example, they could refuse to be transparent by failing to open up their technologies to third-party scrutiny, meaning that it would be impossible to know if providers have baked in sufficient resiliency to carry out banking operations. Modernizing is key, therefore, but it needs to be done cautiously, and with a reliable strategy. For James, the best way forward is to deploy multi-cloud configurations in the financial sector to balance the risk across multiple providers. Only 17% of the financial institutions surveyed by Google have already adopted multi-cloud as an architecture of choice, while 28% rely on single cloud. According to the company, more work needs to be done from a regulatory aspect to incentivize a robust and responsible adoption of cloud among financial organizations. "Consumers' demand for very quick transformation is becoming really overwhelming, and financial services organizations will take shortcuts to deliver on customer expectations as soon as possible," said James.
Federated learning starts with a base machine learning model in the cloud server. This model is either trained on public data (e.g., Wikipedia articles or the ImageNet dataset) or has not been trained at all. In the next stage, several user devices volunteer to train the model. These devices hold user data that is relevant to the model’s application, such as chat logs and keystrokes. These devices download the base model at a suitable time, for instance when they are on a wi-fi network and are connected to a power outlet (training is a compute-intensive operation and will drain the device’s battery if done at an improper time). Then they train the model on the device’s local data. After training, they return the trained model to the server. Popular machine learning algorithms such as deep neural networks and support vector machines is that they are parametric. Once trained, they encode the statistical patterns of their data in numerical parameters and they no longer need the training data for inference. Therefore, when the device sends the trained model back to the server, it doesn’t contain raw user data.
A team of developers won’t be able to suss out all the various bugs in your services, but thousands of users will. And it only takes one to exploit a weakness. While our zealous user was the flapping butterfly wing that lead to the tornado, it was aided and abetted by our own bad assumptions. Fortunately, there are strategies and tools you can use to mitigate these situations. If you’re lucky, you have a Quality Assurance team dedicated to catching bugs. Have you heard the one about a QA tester walking into a bar? Even if you do have a QA team — and especially if you don’t — automated load, end-to-end, and fuzz testing will also help catch those tricky bugs. I would recommend reading Martin Fowler’s article on The Practical Test Pyramid. In the end, APIs are like chainsaws. They are powerful tools intended to that empower our users. But that power needs to come with the necessary safety measures. Without them, your users may end up causing a lot of undue damage to both themselves and you.
Too many organizations lack automated and effective methods to centrally track and manage their relationships with the burgeoning number of third parties with whom they do business. This, coupled with the lack of information organizations have about these third parties, makes them a cybercriminal’s best friend. The recent Presidential Executive Order (EO) mandates the federal government “improve its efforts to identify, deter, protect against, detect, and respond to these actions and actors.” For organizations looking to make changes to their third party identity risk security measures, there are steps they can implement today including: properly identifying who each third party is and the sensitive data to which they have access; conducting regular user audits to ensure third parties have access based on the least amount of privilege necessary to do their jobs; extending zero trust programs to third party non-employees; and conducting continuous risk ratings of the individuals working within a third party vendor or partner, not just the organization as a whole.
DeFi (decentralized finance) technology allows for the inherent convenience of centralized markets without allowing the wealth and governance authority to pool into one person’s wallet. Essentially, DeFi is enabled by the blockchain, which enables permission-less, peer-to-peer transactions. This removes middlemen like banks and other large financial institutions. It lowers costs and technical barriers for entrepreneurs and individuals. Fees, documentation, and legal jurisdictions prevent many people across the world from accessing the financial tools they need to succeed. DeFi platforms circumvent the need for all of these things and allow them to transact in a secure environment. NFTs are the driving force behind a significant portion of the DeFi infrastructure. NFTs aren’t limited to collectibles. They represent programmable bits of data stored on the blockchain. The blockchain provides a transparent, hack-proof storage solution. This equates to ownership over pieces of data that can be programmed to do different things when interacted with.
Digital transformation essentially boils down to unlocking value for customers. McKinsey estimates that digital transformation initiatives that focus on customer-centricity increase customer satisfaction by 20-30% and economic gains by 20-50%. Organisations investing in digital transformation are looking to deliver innovative and seamless customer experiences in real-time. There is a greater focus on customer lifetime value (CLV) and the role of innovative customer experiences on long-term customer value. In a continuously evolving digital ecosystem, with no dearth of choice and convenience, customer behaviours are rapidly changing. In such a world, businesses need a holistic view of the entire customer lifecycle to go beyond transactional interactions and establish trust. Organisations are connecting each step in the customer journey to interact and understand prominent needs and gain an exceptional number of improvement opportunities. This is possible by implementing an automated data collection process and creating a universally available data repository for accurate, traceable, and updated information.
The reason enterprises want to reduce their network-management burden is difficulty in acquiring and maintaining skilled network-operations specialists. This has been a problem for decades; network-operations specialists have no career paths in most enterprises, so they top out in salary and promotion opportunity. Over half of the 59 enterprises I talked with said that they had a problem retaining a network specialist for more than three years, and 12 said they had problems retaining them for two years. Every enterprise said that it took longer to find qualified network specialists than programmers. ... A close second in terms of managed-service drivers was difficulty in supporting remote sites. The problem with remote network support, said 50 of my managed-service enterprises, is that the best way for diagnosis of network problems at remote sites requires that the network be used to project central technology skills to those locations. Obviously, that's Catch-22 in action. This is one reason why SD-WAN is so often associated with managed services; SD-WAN is all about adding small, remote, sites to the company VPN.
While a cloud OS may be attractive to some organizations and users, there will be others that require additional app support that will still require access to a machine with an onboard OS and apps (or at least browser-based access to a different cloud). Many legacy enterprise apps may not run in such an environment and are very unlikely to be migrated. Those users may not be good candidates for a Windows 365 deployment. As a result, I don’t see a cloud OS like Windows 365 becoming the universal (or even dominant) OS anytime soon. The bottom line is, enterprises that are struggling with managing multiple device types (e.g., PC and Macs, Android and iOS, Chromebooks) that need a single access point (and a single license) to apps might find Windows 365 an attractive option over buying multiple licenses and/or managing multiple user device types at substantial costs. Managing a cloud-based OS is far easier than managing installed OS and app combinations. But for most companies, the current limitations of Windows 365, and a need to run many internal mature and legacy apps, will make Windows 365 a future rather than a current option.
It's hard to prove digital identity, and many of the current approaches – such as email + password + SMS PIN codes – add complexity for the user without actually addressing the core issue, which is: can these identities be trusted? As I mentioned before, you can have email addresses that represent your identity online. And you could have multiple [email] addresses – for example, it's easy to get Gmail addresses; they're free, and so bad actors can exploit that freedom. You can have multiple accounts created by using those multiple free email addresses, and bad actors can hide behind them either to commit fraud or just to spread fake news. The trick is very much to have some sort of balance between the freedom and the friction; the freedom and that proven identity. ... But if you can make it something that has an associated security factor – and the phone does this, because it's got the SIM card – then you can have that thing which you're willing to share, but at the same time has a proven credential, and that allows you to build trust associated with that.
Quote for the day:
"Leaders make decisions that create the future they desire." -- Mike Murdock